Navigation functions learning from experiments: Application to anthropomorphic grasping

Filippidis, IF; Kyriakopoulos, KJ; Artemiadis, PK

dc.contributor.author	Filippidis, IF	en
dc.contributor.author	Kyriakopoulos, KJ	en
dc.contributor.author	Artemiadis, PK	en
dc.date.accessioned	2014-03-01T02:53:57Z
dc.date.available	2014-03-01T02:53:57Z
dc.date.issued	2012	en
dc.identifier.issn	10504729	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36496
dc.subject.other	Configuration space	en
dc.subject.other	Navigation functions	en
dc.subject.other	Spline basis functions	en
dc.subject.other	Unknown environments	en
dc.subject.other	Partial differential equations	en
dc.subject.other	Principal component analysis	en
dc.subject.other	Robotics	en
dc.subject.other	Trajectories	en
dc.subject.other	Experiments	en
dc.title	Navigation functions learning from experiments: Application to anthropomorphic grasping	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICRA.2012.6225168	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICRA.2012.6225168	en
heal.identifier.secondary	6225168	en
heal.publicationDate	2012	en
heal.abstract	This paper proposes a method to construct Navigation Functions (NF) from experimental trajectories in an unknown environment. We want to approximate an unknown obstacle function and then use it within an NF. When navigating the same destinations with the experiments, this NF should produce the same trajectories as the experiments. This requirement is equivalent to a partial differential equation (PDE). Solving the PDE yields the unknown obstacle function, expressed with spline basis functions. We apply this new method to anthropomorphic grasping, producing automatic trajectories similar to the observed ones. The grasping experiments were performed for a set of different objects, Principal Component Analysis (PCA) allows reduction of the configuration space dimension, where the learning NF method is then applied. © 2012 IEEE.	en
heal.journalName	Proceedings - IEEE International Conference on Robotics and Automation	en
dc.identifier.doi	10.1109/ICRA.2012.6225168	en
dc.identifier.spage	570	en
dc.identifier.epage	575	en